In the context of real-time control systems, it has become possible to obtain temporal resolutions of microseconds due to the development of embedded systems and the Internet of Things (IoT), the optimization of the use of processor hardware, and the improvement of architectures and real-time operating systems (RTOSs). All of these factors, together with current technological developments, have led to efficient central processing unit (CPU) time usage, guaranteeing both the predictability of thread execution and the satisfaction of the timing constraints required by real-time systems (RTSs). This is mainly due to time sharing in embedded RTSs and the pseudo-parallel execution of tasks in single-processor and multi-processor systems. The non-deterministic behavior triggered by asynchronous external interrupts and events in general is due to the fact that, for most commercial RTOSs, the execution of the same instruction ends in a variable number of cycles, primarily due to hazards. The software implementation of RTOS-specific mechanisms may lead to significant delays that can affect deadline requirements for some RTSs. The main objective of this paper was the design and deployment of innovative solutions to improve the performance of RTOSs by implementing their functions in hardware. The obtained architectures are intended to provide feasible scheduling, even if the total CPU utilization is close to the maximum limit. The contributions made by the authors will be followed by the validation of a high-performing microarchitecture, which is expected to allow a thread context switching time and event response time of only one clock cycle each. The main purpose of the research presented in this paper is to improve these factors of RTSs, as well as the implementation of the hardware structure used for the static and dynamic scheduling of tasks, for RTOS mechanisms specific to resource sharing and intertask communication.
Keywords: fast context switch; hardware RTOS; nMPRA architecture; rapid reaction to stimuli; resource multiplication.